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Toolbar PageRank Gone?

11/3/2012 by 5 Comments

UPDATE: I communicated with Matt Cutts about this post, and here is a portion of what he said in response:

“PageRank option for IE toolbar is available under Toolbar Options (click on wrench icon on right) -> Privacy -> Enhanced features.
You can Turn ON/OFF PageRank by checking/unchecking “Use PageRank to see Google’s view of the importance of a page” option.”

So this means that the current page of instructions on how to enable PageRank in the toolbar is inaccurate. I have asked him when this will be updated and will let you know when I get a response.

Original Post

I was working on an article this morning and wanted to get a screen shot of the Google Toolbar showing PageRank. I normally use Chrome, so I don’t use the Google Toolbar, and the Chrome extension I was using did not show a nice little green bar which is what I wanted for my post. The first thing I did is I opened up Internet Explorer and went to the page to install the Google Toolbar. The install went as expected. So far, so good.

However, I began fishing around in the options menu to find out where to click the box to enable the PageRank meter. I couldn’t find it. Next up, I went to the Google Support Forums to see what I was doing wrong. Here is their page on how to enable the PageRank meter:. The screen shot shows where the checkbox is to enable the feature resides:

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Filed Under: Google, Page Rank, SEO

Negative Political Videos and YouTube: Video with Greg Jarboe

11/1/2012 by Leave a Comment

Eric Enge: Hi, I’m Eric Enge, CEO and founder of Stone Temple Consulting. I’m here today with Greg Jarboe, co-founder and president of SEO-PR, and also author of “YouTube and Video Marketing an Hour a Day.”

Greg Jarboe: Good to be here, Eric.

Eric Enge: Glad to have you, as always. So we’re going to get down and dirty now, right?

Greg Jarboe: Oh, good.

Eric Enge: We’re really going to get into, well, into negative political ads.

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Filed Under: Uncategorized

Getting Started in Content Marketing with Brian Clark

10/8/2012 by 2 Comments

Key Points

  1. People are looking for information first, more than they’re looking for traditional sales messages. The sales experience has to begin with information, which is content.
  2. Content is not a fad. It is a way to attract attention and build a loyal following that turns into actual revenue, profit, growth, and a customer base.
  3. To really make a difference with your content, you must focus on positioning.
  4. Come up with a content strategy that’s related to what you sell and makes you into a likable expert. You have to be interesting enough to take the same old boring content, make it compelling, give people reassurance that you’re the right source and overcome objections.
  5. Copyblogger has always relied on the quality of their content to produce links. It was always social media first, links second and search rankings would result because of this.
  6. Content is becoming a major part of Fortune 500 companies, where you can start to see the emergence of roles such as Chief Content Officer. This shows that the big companies are taking this seriously.
  7. Many small businesses recognize the value of content marketing. The challenge has become implementing the strategy and managing the day-to-day tasks associated with content production.
  8. Copyblogger runs as a software company, but also as a media company. On the media side, they are run similar to an online magazine, with editors, journalists and strict publishing standards. This editorial side of the company serves as their sole marketing function.
  9. You always have to stay relevant to and in tune with the audience, which means you’re constantly doing research.

Full Interview Transcript

Eric Enge: Brian, can you provide a little background on CopyBlogger?

Brian Clark: Copyblogger Media is a software company that provides web-publishing software.

We started as a blog almost seven years ago, in January 2006. I built an audience talking about the very things I was doing to build that audience, and it evolved into a software company over the years. We now have 90,000 customers thanks to the 170,000 subscribers in our audience that allowed us to build our customer base.

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Filed Under: Uncategorized

A Mathematical Model for Assessing Page Quality

9/25/2012 by 8 Comments

Guest Post by Ashutosh Garg

In this article, by page quality we refer to quality of a page with respect to a search query and a user who issued the query.

Page quality is a broad concept and depending upon the actual context in which one plans to use quality score, the actual algorithm will vary. Instead of going into a specific algorithm, this article will present a framework in which to think about page quality and how one can morph it to fit one’s unique situation.

Some of the situations where page quality is used are

  1. Search Engines – search engines score a page with respect to query and use this signal to understand if a page might be relevant to a user’s query or not. Additionally, by assigning a numeric score, one can identify one page is “relatively” better than the other one or not.
  2. Ad Targeting – when showing a particular ad to a user, an adnetwork may score the ad and corresponding landing page against user issued query and use it to identify if the ad is indeed relevant to what user is looking for or not.
  3. Discovery – A page can be evaluated, even in absence of query, to understand its quality and thus identifying if this page should be recommended to end user or not.

In this article we will consider the different algorithms used to assess page quality.

The first set of algorithms will compute the score of the document as a function of the actual query issued by the user –

IR score – Information Retrieval community has been researching how to compute the best possible score for a page given a query. This is probably the most important score one can use in evaluating a page. Various open source search engines like Lucene implemented this algorithm. Given a query Q={q1, q2, q3} containing three words and page P, various steps that are used in computing the score of the page are

  1. Come up with a relative weight of each section of the page – A typical webpage can be divided into various components like – title, headings (H1, H2, H3..,) body, bold text, large text, small text (based on font sizes), text above the fold of the page (assuming a certain display), anchor text, boiler plate text, text on pages being pointed to, text on pages user visited to prior to visiting this page, text present in images on the page, URL text etc. Depending upon the application, one can assign different weight to different elements of the page. One rule of thumb is to see how people are going to discover the page and form their first impression. If it is search – people will discover page by reading the title and snippet displayed by search engines. People will form their first opinions by reading the text above the fold.
  2. Generate features based on query – Take the query and break it down into n–grams (a bigram is all phrases of length two). This is followed by assigning weight to each of these n–grams. For e.g. consider a query – “canon digital camera”. In this query, “canon” is an important unigram as it refers to the brand. “canon digital” is a bad phrase while “digital camera” is a good phrase. Traditionally people have used TFIDF (http://en.wikipedia.org/wiki/Tf*idf ) to come up with a weighting. One thing to be cautious is which dataset that is used to compute TFIDF. It should very closely resemble the dataset where weighting is applied.
  3. Document quality for computing TFIDF score – A document that consists of the content of all the pages on the web will match any query. However, it is not a great experience to come across a very large document. At the same time a document which is identical to query is bad as a user won’t learn anything new when (s)he lands on the page. Review what the platform is used by most of the visitors of your website. If they are using smartphones, ideal document length should be less than 500 words, tablet – 1K words, laptop – even longer given the presentation. Some way of normalizing the score by document length should be used. Various papers have been published in IR community to normalize IR score based on document length.
  4. A simple scoring of a document can be

Page P consists of fields di, with weight wi and query Q consists of words qk. Length of page is L, number of phrases in query is Nq

where f is a normalization element function based on doc length.

Which page has a higher IR Score for “Canon digital camera”?

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Filed Under: Google, Search Engine Algorithms, SEO

Stefan Weitz on Quora Integration and Social Data Sets

9/4/2012 by Leave a Comment

Key Points

  1. Quora is one of the latest networks that Bing has socially integrated into search. Quora helps to disambiguate and make sense of some of the different facets of certain search terms.
  2. The goal of using Quora (and other social integrations Bing is doing) is to replicate the very human characteristic of involving others in decision-making.
  3. Actions, opinions, and recommendations are happening all around us, it’s not as if we need to say anymore or do anymore. We need something (like Bing) to find that little needle in the information haystack and bring it right into your search experience.
  4. Bing is continuing to add more networks to it’s social integration. The focus is to find the best method to expose the networks in a way that fits in the search experience.

Full Interview Transcript

Eric Enge: Hi. I’m Eric Enge, I’m the CEO of Stone Temple Consulting. We are a holistic internet marketing optimization firm. Whatever that is! I’m here again with Stefan Weitz in what’s becoming a regular series of discussions about new social integrations from Bing. How cool is that?

Stefan Weitz: It’s very cool, and Eric, I think you can just basically say you’re the premier digital, online, SEO/SEM, marketing service on the whole planet, and you’d be fine.

Eric Enge: That’s excellent. But, it’s much better when you say it than when I do. So, the case of wine or whatever it is you choose is going to be shipped to you…

Stefan Weitz: I’d like some Metromint water. That would be great.

Eric Enge: Yeah. Here we are, by the way, both showing our unshaven looks. So, I think shows that the search industry remains a casual place to hangout.

Stefan Weitz: I did shower.

Eric Enge: Yes, a brief reintroduction to you would be great.

Stefan Weitz: Sure. My name is Stefan Weitz, as it was last time. I work at Bing. I do a lot of work with start-ups, entrepreneurs, academics, and venture capitalists to really understand where search is going and how to advance the state of the art. Then, I work with the product teams both to help incorporate those things into the product, as well as evangelize those things once they actually reach the product.

Quora LogoEric Enge: Cool. I really like that you’re continuing these social integrations. The latest is Quora. Tell us a little bit about that.

Stefan Weitz: Quora is a great one. It’s one of those things that we looked at. We always, in the back of our head, we wanted to go and tap this data set, because it is such a different set than, say, Facebook or Twitter, or what not. In many cases you get these layers of answers and they’re layers for answers on a variety of topics. I’m just looking at the stream here coming in. I see Jodie Foster was one that had a high Quora. There must have been a discussion on Quora about that.

…Quora expands the canvas of what one could talk about when looking for particular things online.

Now, you could get a bunch of information on Jodie Foster in standard search, and you could even maybe see one of your friends liked the movie she was in with our current implementation of social search in the sidebar. But really, Quora expands the canvas of what one could talk about when looking for particular things online.

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Filed Under: Microsoft, Search Engine Algorithms, Social Web

Stefan Weitz Discusses the True Value of Social Signals

7/30/2012 by 6 Comments

Key Points From The Interview

  1. Bing’s goal is to make social signals more valuable by presenting them in a way that actually augments the search experience.
  2. Previously, most social information was trapped in people’s heads. Now, they are publicly expressing this information in a way that machines are able to read it and make use of it.
  3. Likes are a good signal, but they’re not a granular signal of what particular thing you’re actually expressing a like about.
  4. Social integration in search is more than simply looking at a like and then showing the liked item. It is about taking that social data and creating a profile that can then be used to add more value to the search experience.
  5. While Google is trying to build their own social network, Bing prefers to partner with and integrate with social media companies that are already doing amazing work in their respective niche.

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Filed Under: Microsoft, SEO, Social Web
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